queG

QueG is a fictional open-source software framework described in instructional materials as a modular toolkit for processing graph queries and analytics. It is presented as a standalone project with an emphasis on extensibility and explainability. This article treats QueG as a hypothetical example rather than a claim of existing software.

QueG's architecture centers on a core execution engine that interprets graph queries, a flexible data model for labeled property graphs, and a pluggable optimizer that can be extended via plugins. The design emphasizes portability across platforms and clear separation of concerns.

Architecture and components: The core engine executes a high-level query language, with components for parsing, plan generation, and runtime operators. A plugin system allows data sources, storage backends, and custom operators to be integrated. QueG also includes a lightweight catalog for schema and metadata.

History and status: QueG originated in classroom and textbook examples used to illustrate graph-query architectures. There are no official releases, maintainers, or large-scale deployments in this hypothetical context.

Potential applications: Theoretical research into query optimization, teaching material for database courses, benchmarking of graph-query workloads, and demonstration of plugin-based architectures.